Lediga job som Filosof

Automated Image Analysis for Advanced Metabolic Phenotyping in Obesity and Diabetes

About the Project:

You will join PREFERENCE, an international Marie Skłodowska-Curie doctoral network dedicated to advancing large axial field of view (LAFOV) PET/CT imaging. PREFERENCE brings together 12 academic institutions and several industrial partners with extensive expertise in quantitative imaging, image analysis and imaging technology.

A highly innovative system, called long axial field of view (LAFOV) PET/CT, has become available and is the ideal medical imaging modality to study diseases and molecular processes at the whole body/systems biology level with multiple radiotracers. Studying diseases and diagnosing patients using PET/CT imaging should use a whole body/systems biology approach, i.e., a comprehensive whole-body characterization of disease, and it should be longitudinal and should use multiple radiotracers. However, LAFOV PET/CT is so new that we lack the necessary tools, methodologies, imaging procedures and skilled scientists to effectively address key applications in patient care and research. With the PREFERENCE project we aim to develop innovative LAFOV PET/CT methodologies to perform and support ground-breaking new clinical research.

PREFERENCE will train the next generation of researchers specialized in LAFOV PET/CT who will capitalize on the new clinical and research opportunities of the LAFOV PET/CT system. By performing research in both academia and industrial groups, researchers within PREFERENCE receive training in a unique combination of (soft) skills across disciplines and sectors. PREFERENCE will develop new LAFOV PET/CT methodologies and perform LAFOV PET/CT clinical studies across disease areas to obtain novel biological insights. This project was selected by the EU as worthy of funding under the H2025 Marie Sklodowska Curie awards. The consortium consists of 12 academic partners with a strong expertise in quantitative (LAFOV) PET/CT imaging as well as industrial partners developing imaging equipment or providing multi-center image analysis solutions and services.

About the PhD Position:

This is a 4-year full time position as an early stage researcher (ESR) under the auspice of the MSCA DN programme. The successful candidate will have a software background and interest in medical imaging. The candidate will develop tools for accurate analysis of whole-body metabolic imaging, including insulin sensitivity and perfusion assessment and develop spatial correlation tools for visual and quantitative comparisons. The candidate will then apply this to clinical trial data to aid in understanding the multiplexed data and characterise groups with and without metabolic disease, as well as study differences in end organ involvement between sexes, disease states, and other parameters. The aim is to achieve advanced metabolic phenotyping in obesity and diabetes to improve understanding the relationship to mechanisms in relation to end organ damage.

Within the course of this project, there will be 1-month secondments to PREFERENCE partners Aarhus, Copenhagen and Vienna for subprojects and data and software exchange facilitation.

You will receive a monthly gross allowance starting at €2900 - €3100, with an annual increase throughout the programme. The allowance is based on criteria set by the PREFERENCE programme and adjusted with a country-specific correction factor. If applicable, fellows may also be eligible for an additional family allowance of €300 - €360 per month.

Requirements and Qualifications:

To meet the entry requirements for doctoral studies, you must have:

• Successfully completed studies in Physics, Biomedical Engineering, Computer Science or alike (MSc degree or equivalent)

• Very good command of the English language

• Good communication skills (a pre-requisite for cooperating in a multi-disciplinary environment)

• Willingness to travel and flexibility to arrange that in predetermined time

• Proficiency in Python for medical image analysis will be of benefit, and proficiency in C/C++ or similar for efficient management of large images will be of benefit

• Prior experience with medical imaging, CT, PET, MRI, image analysis, and software development will be of benefit.

Note: Important strict eligibility criteria according to MARIE SKLODOWSKA CURIE programs:

Recruitment process:

After assessing compliance with the mobility rule and eligibility for the position based on your Europass CV, motivation letter, and answer to mandatory questions, the selection of the candidates and invitation for the interviews will be done by Antaros. The recruitment process will include online interviews with key stakeholders from Antaros Medical, an international scientific mentor from the network, and a business coach.

As part of the recruitment process, your application will be shared with the PREFERENCE project coordinator for the purpose of verifying eligibility criteria, centralized coordination, and registration of the recruitment process.

You application may also be shared with supervisors at other partner institutions and organisations to assess suitability for similar doctoral positions within the network. Such sharing will only take place in accordance with applicable data protection legislation and the candidate's consent.

Applications should be submitted online by 18 October 2026.

In case of any questions regarding the PhD project, please contact: joel.kullberg@antarosmedical.com

In case of any procedural questions, please contact the coordinator: preference@amsterdamumc.nl

Automated Image Analysis for Advanced Metabolic Phenotyping in Obesity and Diabetes

About the Project:

You will join PREFERENCE, an international Marie Skłodowska-Curie doctoral network dedicated to advancing large axial field of view (LAFOV) PET/CT imaging. PREFERENCE brings together 12 academic institutions and several industrial partners with extensive expertise in quantitative imaging, image analysis and imaging technology.

A highly innovative system, called long axial field of view (LAFOV) PET/CT, has become available and is the ideal medical imaging modality to study diseases and molecular processes at the whole body/systems biology level with multiple radiotracers. Studying diseases and diagnosing patients using PET/CT imaging should use a whole body/systems biology approach, i.e., a comprehensive whole-body characterization of disease, and it should be longitudinal and should use multiple radiotracers. However, LAFOV PET/CT is so new that we lack the necessary tools, methodologies, imaging procedures and skilled scientists to effectively address key applications in patient care and research. With the PREFERENCE project we aim to develop innovative LAFOV PET/CT methodologies to perform and support ground-breaking new clinical research.

PREFERENCE will train the next generation of researchers specialized in LAFOV PET/CT who will capitalize on the new clinical and research opportunities of the LAFOV PET/CT system. By performing research in both academia and industrial groups, researchers within PREFERENCE receive training in a unique combination of (soft) skills across disciplines and sectors. PREFERENCE will develop new LAFOV PET/CT methodologies and perform LAFOV PET/CT clinical studies across disease areas to obtain novel biological insights. This project was selected by the EU as worthy of funding under the H2025 Marie Sklodowska Curie awards. The consortium consists of 12 academic partners with a strong expertise in quantitative (LAFOV) PET/CT imaging as well as industrial partners developing imaging equipment or providing multi-center image analysis solutions and services.

About the PhD Position:

This is a 4-year full time position as an early stage researcher (ESR) under the auspice of the MSCA DN programme. The successful candidate will have a software background and interest in medical imaging. The candidate will develop tools for accurate analysis of whole-body metabolic imaging, including insulin sensitivity and perfusion assessment and develop spatial correlation tools for visual and quantitative comparisons. The candidate will then apply this to clinical trial data to aid in understanding the multiplexed data and characterise groups with and without metabolic disease, as well as study differences in end organ involvement between sexes, disease states, and other parameters. The aim is to achieve advanced metabolic phenotyping in obesity and diabetes to improve understanding the relationship to mechanisms in relation to end organ damage.

Within the course of this project, there will be 1-month secondments to PREFERENCE partners Aarhus, Copenhagen and Vienna for subprojects and data and software exchange facilitation.

You will receive a monthly gross allowance starting at €2900 - €3100, with an annual increase throughout the programme. The allowance is based on criteria set by the PREFERENCE programme and adjusted with a country-specific correction factor. If applicable, fellows may also be eligible for an additional family allowance of €300 - €360 per month.

Requirements and Qualifications:

To meet the entry requirements for doctoral studies, you must have:

• Successfully completed studies in Physics, Biomedical Engineering, Computer Science or alike (MSc degree or equivalent)

• Very good command of the English language

• Good communication skills (a pre-requisite for cooperating in a multi-disciplinary environment)

• Willingness to travel and flexibility to arrange that in predetermined time

• Proficiency in Python for medical image analysis will be of benefit, and proficiency in C/C++ or similar for efficient management of large images will be of benefit

• Prior experience with medical imaging, CT, PET, MRI, image analysis, and software development will be of benefit.

Note: Important strict eligibility criteria according to MARIE SKLODOWSKA CURIE programs:

Recruitment process:

After assessing compliance with the mobility rule and eligibility for the position based on your Europass CV, motivation letter, and answer to mandatory questions, the selection of the candidates and invitation for the interviews will be done by Antaros. The recruitment process will include online interviews with key stakeholders from Antaros Medical, an international scientific mentor from the network, and a business coach.

As part of the recruitment process, your application will be shared with the PREFERENCE project coordinator for the purpose of verifying eligibility criteria, centralized coordination, and registration of the recruitment process.

You application may also be shared with supervisors at other partner institutions and organisations to assess suitability for similar doctoral positions within the network. Such sharing will only take place in accordance with applicable data protection legislation and the candidate's consent.

Applications should be submitted online by 18 October 2026.

In case of any questions regarding the PhD project, please contact: joel.kullberg@antarosmedical.com

In case of any procedural questions, please contact the coordinator: preference@amsterdamumc.nl

Automated Image Analysis for Advanced Metabolic Phenotyping in Obesity and Diabetes

About the Project:

You will join PREFERENCE, an international Marie Skłodowska-Curie doctoral network dedicated to advancing large axial field of view (LAFOV) PET/CT imaging. PREFERENCE brings together 12 academic institutions and several industrial partners with extensive expertise in quantitative imaging, image analysis and imaging technology.

A highly innovative system, called long axial field of view (LAFOV) PET/CT, has become available and is the ideal medical imaging modality to study diseases and molecular processes at the whole body/systems biology level with multiple radiotracers. Studying diseases and diagnosing patients using PET/CT imaging should use a whole body/systems biology approach, i.e., a comprehensive whole-body characterization of disease, and it should be longitudinal and should use multiple radiotracers. However, LAFOV PET/CT is so new that we lack the necessary tools, methodologies, imaging procedures and skilled scientists to effectively address key applications in patient care and research. With the PREFERENCE project we aim to develop innovative LAFOV PET/CT methodologies to perform and support ground-breaking new clinical research.

PREFERENCE will train the next generation of researchers specialized in LAFOV PET/CT who will capitalize on the new clinical and research opportunities of the LAFOV PET/CT system. By performing research in both academia and industrial groups, researchers within PREFERENCE receive training in a unique combination of (soft) skills across disciplines and sectors. PREFERENCE will develop new LAFOV PET/CT methodologies and perform LAFOV PET/CT clinical studies across disease areas to obtain novel biological insights. This project was selected by the EU as worthy of funding under the H2025 Marie Sklodowska Curie awards. The consortium consists of 12 academic partners with a strong expertise in quantitative (LAFOV) PET/CT imaging as well as industrial partners developing imaging equipment or providing multi-center image analysis solutions and services.

About the PhD Position:

This is a 4-year full time position as an early stage researcher (ESR) under the auspice of the MSCA DN programme. The successful candidate will have a software background and interest in medical imaging. The candidate will develop tools for accurate analysis of whole-body metabolic imaging, including insulin sensitivity and perfusion assessment and develop spatial correlation tools for visual and quantitative comparisons. The candidate will then apply this to clinical trial data to aid in understanding the multiplexed data and characterise groups with and without metabolic disease, as well as study differences in end organ involvement between sexes, disease states, and other parameters. The aim is to achieve advanced metabolic phenotyping in obesity and diabetes to improve understanding the relationship to mechanisms in relation to end organ damage.

Within the course of this project, there will be 1-month secondments to PREFERENCE partners Aarhus, Copenhagen and Vienna for subprojects and data and software exchange facilitation.

You will receive a monthly gross allowance starting at €2900 - €3100, with an annual increase throughout the programme. The allowance is based on criteria set by the PREFERENCE programme and adjusted with a country-specific correction factor. If applicable, fellows may also be eligible for an additional family allowance of €300 - €360 per month.

Requirements and Qualifications:

To meet the entry requirements for doctoral studies, you must have:

• Successfully completed studies in Physics, Biomedical Engineering, Computer Science or alike (MSc degree or equivalent)

• Very good command of the English language

• Good communication skills (a pre-requisite for cooperating in a multi-disciplinary environment)

• Willingness to travel and flexibility to arrange that in predetermined time

• Proficiency in Python for medical image analysis will be of benefit, and proficiency in C/C++ or similar for efficient management of large images will be of benefit

• Prior experience with medical imaging, CT, PET, MRI, image analysis, and software development will be of benefit.

Note: Important strict eligibility criteria according to MARIE SKLODOWSKA CURIE programs:

Recruitment process:

After assessing compliance with the mobility rule and eligibility for the position based on your Europass CV, motivation letter, and answer to mandatory questions, the selection of the candidates and invitation for the interviews will be done by Antaros. The recruitment process will include online interviews with key stakeholders from Antaros Medical, an international scientific mentor from the network, and a business coach.

As part of the recruitment process, your application will be shared with the PREFERENCE project coordinator for the purpose of verifying eligibility criteria, centralized coordination, and registration of the recruitment process.

You application may also be shared with supervisors at other partner institutions and organisations to assess suitability for similar doctoral positions within the network. Such sharing will only take place in accordance with applicable data protection legislation and the candidate's consent.

Applications should be submitted online by 18 October 2026.

In case of any questions regarding the PhD project, please contact: joel.kullberg@antarosmedical.com

In case of any procedural questions, please contact the coordinator: preference@amsterdamumc.nl

Automated Image Analysis for Advanced Metabolic Phenotyping in Obesity and Diabetes

About the Project:

You will join PREFERENCE, an international Marie Skłodowska-Curie doctoral network dedicated to advancing large axial field of view (LAFOV) PET/CT imaging. PREFERENCE brings together 12 academic institutions and several industrial partners with extensive expertise in quantitative imaging, image analysis and imaging technology.

A highly innovative system, called long axial field of view (LAFOV) PET/CT, has become available and is the ideal medical imaging modality to study diseases and molecular processes at the whole body/systems biology level with multiple radiotracers. Studying diseases and diagnosing patients using PET/CT imaging should use a whole body/systems biology approach, i.e., a comprehensive whole-body characterization of disease, and it should be longitudinal and should use multiple radiotracers. However, LAFOV PET/CT is so new that we lack the necessary tools, methodologies, imaging procedures and skilled scientists to effectively address key applications in patient care and research. With the PREFERENCE project we aim to develop innovative LAFOV PET/CT methodologies to perform and support ground-breaking new clinical research.

PREFERENCE will train the next generation of researchers specialized in LAFOV PET/CT who will capitalize on the new clinical and research opportunities of the LAFOV PET/CT system. By performing research in both academia and industrial groups, researchers within PREFERENCE receive training in a unique combination of (soft) skills across disciplines and sectors. PREFERENCE will develop new LAFOV PET/CT methodologies and perform LAFOV PET/CT clinical studies across disease areas to obtain novel biological insights. This project was selected by the EU as worthy of funding under the H2025 Marie Sklodowska Curie awards. The consortium consists of 12 academic partners with a strong expertise in quantitative (LAFOV) PET/CT imaging as well as industrial partners developing imaging equipment or providing multi-center image analysis solutions and services.

About the PhD Position:

This is a 4-year full time position as an early stage researcher (ESR) under the auspice of the MSCA DN programme. The successful candidate will have a software background and interest in medical imaging. The candidate will develop tools for accurate analysis of whole-body metabolic imaging, including insulin sensitivity and perfusion assessment and develop spatial correlation tools for visual and quantitative comparisons. The candidate will then apply this to clinical trial data to aid in understanding the multiplexed data and characterise groups with and without metabolic disease, as well as study differences in end organ involvement between sexes, disease states, and other parameters. The aim is to achieve advanced metabolic phenotyping in obesity and diabetes to improve understanding the relationship to mechanisms in relation to end organ damage.

Within the course of this project, there will be 1-month secondments to PREFERENCE partners Aarhus, Copenhagen and Vienna for subprojects and data and software exchange facilitation.

You will receive a monthly gross allowance starting at €2900 - €3100, with an annual increase throughout the programme. The allowance is based on criteria set by the PREFERENCE programme and adjusted with a country-specific correction factor. If applicable, fellows may also be eligible for an additional family allowance of €300 - €360 per month.

Requirements and Qualifications:

To meet the entry requirements for doctoral studies, you must have:

• Successfully completed studies in Physics, Biomedical Engineering, Computer Science or alike (MSc degree or equivalent)

• Very good command of the English language

• Good communication skills (a pre-requisite for cooperating in a multi-disciplinary environment)

• Willingness to travel and flexibility to arrange that in predetermined time

• Proficiency in Python for medical image analysis will be of benefit, and proficiency in C/C++ or similar for efficient management of large images will be of benefit

• Prior experience with medical imaging, CT, PET, MRI, image analysis, and software development will be of benefit.

Note: Important strict eligibility criteria according to MARIE SKLODOWSKA CURIE programs:

Recruitment process:

After assessing compliance with the mobility rule and eligibility for the position based on your Europass CV, motivation letter, and answer to mandatory questions, the selection of the candidates and invitation for the interviews will be done by Antaros. The recruitment process will include online interviews with key stakeholders from Antaros Medical, an international scientific mentor from the network, and a business coach.

As part of the recruitment process, your application will be shared with the PREFERENCE project coordinator for the purpose of verifying eligibility criteria, centralized coordination, and registration of the recruitment process.

You application may also be shared with supervisors at other partner institutions and organisations to assess suitability for similar doctoral positions within the network. Such sharing will only take place in accordance with applicable data protection legislation and the candidate's consent.

Applications should be submitted online by 18 October 2026.

In case of any questions regarding the PhD project, please contact: joel.kullberg@antarosmedical.com

In case of any procedural questions, please contact the coordinator: preference@amsterdamumc.nl

Elektrifiering och digitalisering tillhör framtidens största områden för omställning till hållbara samhällen. Institutionen för elektroteknik bedriver framgångsrik forskning och utbildning inom dessa områden – däribland förnybara energikällor och elfordon, industriell IoT, 6G kommunikation och trådlösa sensornät men även forskning och utbildning inom Life Science, hälsoteknik, smarta elektroniska sensorer och medicinska system. Institutionen för elektroteknik är en internationell miljö med ca 170 medarbetare som bidrar till viktiga tekniska energi- och hälsolösningar vid Ångströmlaboratoriet.

Vi söker nu en Doktorand i resilienta elkraftsystem.

Kom och jobba med oss!

Tjänsten är placerad vid avdelningen för elektricitetslära inom institutionen för elektroteknik. Här hittar du en trevlig arbetsmiljö med ett aktivt doktorandnätverk och en mängd experimentella projekt. Avdelningen samarbetar med svenska företag – både offentliga och privata – samt andra intressenter inom de olika forskningsområdena. Vi ser fram emot din ansökan. Var med och bygg framtiden med oss!

Läs mer om våra förmåner och hur det är att jobba inom Uppsala.

Projektbeskrivning

Elkraftsystemets betydelse för samhällets funktion ställer ökade krav på robusthet, återhämtningsförmåga och effektiv drift, särskilt i ljuset av ett försämrat säkerhetsläge, ökad elektrifiering och ett högre nyttjande av befintliga transmissions- och distributionsnät av el. Inom dessa doktorandprojekt kommer avancerad modellering, systemsimuleringar och scenarioanalyser att användas för att utveckla metoder som stärker elkraftsystemets resiliens vid kris, krig och andra ansträngda driftförhållanden.

Projekten omfattar såväl optimerad drift av elkraftsystemet efter omfattande störningar som utveckling av nya nyckeltal, prognosmetoder och styrstrategier för att mäta, analysera och förbättra elkraftsystemets förmåga att upprätthålla leveransen av el under ansträngda förhållanden. Arbetet sker i nära samverkan med energibranschen och omfattar tillämpningar i simuleringsverktyg. Projekten genomförs inom kompetenscentret RESILIENT, ett nationellt forskningscentrum som samlar akademi, industri och samhällsaktörer för att utveckla framtidens resilienta och hållbara energisystem genom nära samverkan mellan forskning och tillämning.

Arbetsuppgifter

• Bedriva forskning inom resilienta elkraftsystem med fokus på elsystemets funktion, drift och återgång under kris-, krigs- och andra ansträngda driftförhållanden.
• Utveckla metoder, modeller och beslutsstöd för att stärka elkraftsystemets robusthet, resiliens och återhämtningsförmåga.
• Genomföra teoretiska studier i kombination med modellutveckling, systemsimuleringar och scenarioanalyser för att validera forskningsresultat.
• Använda och vidareutveckla modeller i simuleringsverktyg såsom PowerFactory, PowerWorld och PSS®E eller motsvarande.
• Analysera frågor kopplade till systemdrift, systemåterhämtning, resiliensmått, prognoser och styrstrategier för framtidens elkraftsystem.
• Publicera forskningsresultat i vetenskapliga tidskrifter och presentera resultaten vid nationella och internationella konferenser.
• Samverka med industri, myndigheter och andra forskningsaktörer inom kompetenscentret RESILIENT.

Undervisning och övrig institutionstjänstgöring kan komma att ingå i arbetsuppgifterna, dock max 20% av arbetstiden.

Observera att detta är en förkortad version av annonsen. För att se den fullständiga annonsen vänligen klicka på ”Ansök här” eller se Uppsala universitets hemsida:https://uu.se/jobb/

Automated Image Analysis for Advanced Metabolic Phenotyping in Obesity and Diabetes

About the Project:

You will join PREFERENCE, an international Marie Skłodowska-Curie doctoral network dedicated to advancing large axial field of view (LAFOV) PET/CT imaging. PREFERENCE brings together 12 academic institutions and several industrial partners with extensive expertise in quantitative imaging, image analysis and imaging technology.

A highly innovative system, called long axial field of view (LAFOV) PET/CT, has become available and is the ideal medical imaging modality to study diseases and molecular processes at the whole body/systems biology level with multiple radiotracers. Studying diseases and diagnosing patients using PET/CT imaging should use a whole body/systems biology approach, i.e., a comprehensive whole-body characterization of disease, and it should be longitudinal and should use multiple radiotracers. However, LAFOV PET/CT is so new that we lack the necessary tools, methodologies, imaging procedures and skilled scientists to effectively address key applications in patient care and research. With the PREFERENCE project we aim to develop innovative LAFOV PET/CT methodologies to perform and support ground-breaking new clinical research.

PREFERENCE will train the next generation of researchers specialized in LAFOV PET/CT who will capitalize on the new clinical and research opportunities of the LAFOV PET/CT system. By performing research in both academia and industrial groups, researchers within PREFERENCE receive training in a unique combination of (soft) skills across disciplines and sectors. PREFERENCE will develop new LAFOV PET/CT methodologies and perform LAFOV PET/CT clinical studies across disease areas to obtain novel biological insights. This project was selected by the EU as worthy of funding under the H2025 Marie Sklodowska Curie awards. The consortium consists of 12 academic partners with a strong expertise in quantitative (LAFOV) PET/CT imaging as well as industrial partners developing imaging equipment or providing multi-center image analysis solutions and services.

About the PhD Position:

This is a 4-year full time position as an early stage researcher (ESR) under the auspice of the MSCA DN programme. The successful candidate will have a software background and interest in medical imaging. The candidate will develop tools for accurate analysis of whole-body metabolic imaging, including insulin sensitivity and perfusion assessment and develop spatial correlation tools for visual and quantitative comparisons. The candidate will then apply this to clinical trial data to aid in understanding the multiplexed data and characterise groups with and without metabolic disease, as well as study differences in end organ involvement between sexes, disease states, and other parameters. The aim is to achieve advanced metabolic phenotyping in obesity and diabetes to improve understanding the relationship to mechanisms in relation to end organ damage.

Within the course of this project, there will be 1-month secondments to PREFERENCE partners Aarhus, Copenhagen and Vienna for subprojects and data and software exchange facilitation.

You will receive a monthly gross allowance starting at €2900 - €3100, with an annual increase throughout the programme. The allowance is based on criteria set by the PREFERENCE programme and adjusted with a country-specific correction factor. If applicable, fellows may also be eligible for an additional family allowance of €300 - €360 per month.

Requirements and Qualifications:

To meet the entry requirements for doctoral studies, you must have:

• Successfully completed studies in Physics, Biomedical Engineering, Computer Science or alike (MSc degree or equivalent)

• Very good command of the English language

• Good communication skills (a pre-requisite for cooperating in a multi-disciplinary environment)

• Willingness to travel and flexibility to arrange that in predetermined time

• Proficiency in Python for medical image analysis will be of benefit, and proficiency in C/C++ or similar for efficient management of large images will be of benefit

• Prior experience with medical imaging, CT, PET, MRI, image analysis, and software development will be of benefit.

Note: Important strict eligibility criteria according to MARIE SKLODOWSKA CURIE programs:

Recruitment process:

After assessing compliance with the mobility rule and eligibility for the position based on your Europass CV, motivation letter, and answer to mandatory questions, the selection of the candidates and invitation for the interviews will be done by Antaros. The recruitment process will include online interviews with key stakeholders from Antaros Medical, an international scientific mentor from the network, and a business coach.

As part of the recruitment process, your application will be shared with the PREFERENCE project coordinator for the purpose of verifying eligibility criteria, centralized coordination, and registration of the recruitment process.

You application may also be shared with supervisors at other partner institutions and organisations to assess suitability for similar doctoral positions within the network. Such sharing will only take place in accordance with applicable data protection legislation and the candidate's consent.

Applications should be submitted online by 18 October 2026.

In case of any questions regarding the PhD project, please contact: joel.kullberg@antarosmedical.com

In case of any procedural questions, please contact the coordinator: preference@amsterdamumc.nl

Elektrifiering och digitalisering tillhör framtidens största områden för omställning till hållbara samhällen. Institutionen för elektroteknik bedriver framgångsrik forskning och utbildning inom dessa områden – däribland förnybara energikällor och elfordon, industriell IoT, 6G kommunikation och trådlösa sensornät men även forskning och utbildning inom Life Science, hälsoteknik, smarta elektroniska sensorer och medicinska system. Institutionen för elektroteknik är en internationell miljö med ca 170 medarbetare som bidrar till viktiga tekniska energi- och hälsolösningar vid Ångströmlaboratoriet.

Vi söker nu en Doktorand i resilienta elkraftsystem.

Kom och jobba med oss!

Tjänsten är placerad vid avdelningen för elektricitetslära inom institutionen för elektroteknik. Här hittar du en trevlig arbetsmiljö med ett aktivt doktorandnätverk och en mängd experimentella projekt. Avdelningen samarbetar med svenska företag – både offentliga och privata – samt andra intressenter inom de olika forskningsområdena. Vi ser fram emot din ansökan. Var med och bygg framtiden med oss!

Läs mer om våra förmåner och hur det är att jobba inom Uppsala.

Projektbeskrivning

Elkraftsystemets betydelse för samhällets funktion ställer ökade krav på robusthet, återhämtningsförmåga och effektiv drift, särskilt i ljuset av ett försämrat säkerhetsläge, ökad elektrifiering och ett högre nyttjande av befintliga transmissions- och distributionsnät av el. Inom dessa doktorandprojekt kommer avancerad modellering, systemsimuleringar och scenarioanalyser att användas för att utveckla metoder som stärker elkraftsystemets resiliens vid kris, krig och andra ansträngda driftförhållanden.

Projekten omfattar såväl optimerad drift av elkraftsystemet efter omfattande störningar som utveckling av nya nyckeltal, prognosmetoder och styrstrategier för att mäta, analysera och förbättra elkraftsystemets förmåga att upprätthålla leveransen av el under ansträngda förhållanden. Arbetet sker i nära samverkan med energibranschen och omfattar tillämpningar i simuleringsverktyg. Projekten genomförs inom kompetenscentret RESILIENT, ett nationellt forskningscentrum som samlar akademi, industri och samhällsaktörer för att utveckla framtidens resilienta och hållbara energisystem genom nära samverkan mellan forskning och tillämning.

Arbetsuppgifter

• Bedriva forskning inom resilienta elkraftsystem med fokus på elsystemets funktion, drift och återgång under kris-, krigs- och andra ansträngda driftförhållanden.
• Utveckla metoder, modeller och beslutsstöd för att stärka elkraftsystemets robusthet, resiliens och återhämtningsförmåga.
• Genomföra teoretiska studier i kombination med modellutveckling, systemsimuleringar och scenarioanalyser för att validera forskningsresultat.
• Använda och vidareutveckla modeller i simuleringsverktyg såsom PowerFactory, PowerWorld och PSS®E eller motsvarande.
• Analysera frågor kopplade till systemdrift, systemåterhämtning, resiliensmått, prognoser och styrstrategier för framtidens elkraftsystem.
• Publicera forskningsresultat i vetenskapliga tidskrifter och presentera resultaten vid nationella och internationella konferenser.
• Samverka med industri, myndigheter och andra forskningsaktörer inom kompetenscentret RESILIENT.

Undervisning och övrig institutionstjänstgöring kan komma att ingå i arbetsuppgifterna, dock max 20% av arbetstiden.

Observera att detta är en förkortad version av annonsen. För att se den fullständiga annonsen vänligen klicka på ”Ansök här” eller se Uppsala universitets hemsida:https://uu.se/jobb/

Automated Image Analysis for Advanced Metabolic Phenotyping in Obesity and Diabetes

About the Project:

You will join PREFERENCE, an international Marie Skłodowska-Curie doctoral network dedicated to advancing large axial field of view (LAFOV) PET/CT imaging. PREFERENCE brings together 12 academic institutions and several industrial partners with extensive expertise in quantitative imaging, image analysis and imaging technology.

A highly innovative system, called long axial field of view (LAFOV) PET/CT, has become available and is the ideal medical imaging modality to study diseases and molecular processes at the whole body/systems biology level with multiple radiotracers. Studying diseases and diagnosing patients using PET/CT imaging should use a whole body/systems biology approach, i.e., a comprehensive whole-body characterization of disease, and it should be longitudinal and should use multiple radiotracers. However, LAFOV PET/CT is so new that we lack the necessary tools, methodologies, imaging procedures and skilled scientists to effectively address key applications in patient care and research. With the PREFERENCE project we aim to develop innovative LAFOV PET/CT methodologies to perform and support ground-breaking new clinical research.

PREFERENCE will train the next generation of researchers specialized in LAFOV PET/CT who will capitalize on the new clinical and research opportunities of the LAFOV PET/CT system. By performing research in both academia and industrial groups, researchers within PREFERENCE receive training in a unique combination of (soft) skills across disciplines and sectors. PREFERENCE will develop new LAFOV PET/CT methodologies and perform LAFOV PET/CT clinical studies across disease areas to obtain novel biological insights. This project was selected by the EU as worthy of funding under the H2025 Marie Sklodowska Curie awards. The consortium consists of 12 academic partners with a strong expertise in quantitative (LAFOV) PET/CT imaging as well as industrial partners developing imaging equipment or providing multi-center image analysis solutions and services.

About the PhD Position:

This is a 4-year full time position as an early stage researcher (ESR) under the auspice of the MSCA DN programme. The successful candidate will have a software background and interest in medical imaging. The candidate will develop tools for accurate analysis of whole-body metabolic imaging, including insulin sensitivity and perfusion assessment and develop spatial correlation tools for visual and quantitative comparisons. The candidate will then apply this to clinical trial data to aid in understanding the multiplexed data and characterise groups with and without metabolic disease, as well as study differences in end organ involvement between sexes, disease states, and other parameters. The aim is to achieve advanced metabolic phenotyping in obesity and diabetes to improve understanding the relationship to mechanisms in relation to end organ damage.

Within the course of this project, there will be 1-month secondments to PREFERENCE partners Aarhus, Copenhagen and Vienna for subprojects and data and software exchange facilitation.

You will receive a monthly gross allowance starting at €2900 - €3100, with an annual increase throughout the programme. The allowance is based on criteria set by the PREFERENCE programme and adjusted with a country-specific correction factor. If applicable, fellows may also be eligible for an additional family allowance of €300 - €360 per month.

Requirements and Qualifications:

To meet the entry requirements for doctoral studies, you must have:

• Successfully completed studies in Physics, Biomedical Engineering, Computer Science or alike (MSc degree or equivalent)

• Very good command of the English language

• Good communication skills (a pre-requisite for cooperating in a multi-disciplinary environment)

• Willingness to travel and flexibility to arrange that in predetermined time

• Proficiency in Python for medical image analysis will be of benefit, and proficiency in C/C++ or similar for efficient management of large images will be of benefit

• Prior experience with medical imaging, CT, PET, MRI, image analysis, and software development will be of benefit.

Note: Important strict eligibility criteria according to MARIE SKLODOWSKA CURIE programs:

Recruitment process:

After assessing compliance with the mobility rule and eligibility for the position based on your Europass CV, motivation letter, and answer to mandatory questions, the selection of the candidates and invitation for the interviews will be done by Antaros. The recruitment process will include online interviews with key stakeholders from Antaros Medical, an international scientific mentor from the network, and a business coach.

As part of the recruitment process, your application will be shared with the PREFERENCE project coordinator for the purpose of verifying eligibility criteria, centralized coordination, and registration of the recruitment process.

You application may also be shared with supervisors at other partner institutions and organisations to assess suitability for similar doctoral positions within the network. Such sharing will only take place in accordance with applicable data protection legislation and the candidate's consent.

Applications should be submitted online by 18 October 2026.

In case of any questions regarding the PhD project, please contact: joel.kullberg@antarosmedical.com

In case of any procedural questions, please contact the coordinator: preference@amsterdamumc.nl

Elektrifiering och digitalisering tillhör framtidens största områden för omställning till hållbara samhällen. Institutionen för elektroteknik bedriver framgångsrik forskning och utbildning inom dessa områden – däribland förnybara energikällor och elfordon, industriell IoT, 6G kommunikation och trådlösa sensornät men även forskning och utbildning inom Life Science, hälsoteknik, smarta elektroniska sensorer och medicinska system. Institutionen för elektroteknik är en internationell miljö med ca 170 medarbetare som bidrar till viktiga tekniska energi- och hälsolösningar vid Ångströmlaboratoriet.

Vi söker nu en Doktorand i resilienta elkraftsystem.

Kom och jobba med oss!

Tjänsten är placerad vid avdelningen för elektricitetslära inom institutionen för elektroteknik. Här hittar du en trevlig arbetsmiljö med ett aktivt doktorandnätverk och en mängd experimentella projekt. Avdelningen samarbetar med svenska företag – både offentliga och privata – samt andra intressenter inom de olika forskningsområdena. Vi ser fram emot din ansökan. Var med och bygg framtiden med oss!

Läs mer om våra förmåner och hur det är att jobba inom Uppsala.

Projektbeskrivning

Elkraftsystemets betydelse för samhällets funktion ställer ökade krav på robusthet, återhämtningsförmåga och effektiv drift, särskilt i ljuset av ett försämrat säkerhetsläge, ökad elektrifiering och ett högre nyttjande av befintliga transmissions- och distributionsnät av el. Inom dessa doktorandprojekt kommer avancerad modellering, systemsimuleringar och scenarioanalyser att användas för att utveckla metoder som stärker elkraftsystemets resiliens vid kris, krig och andra ansträngda driftförhållanden.

Projekten omfattar såväl optimerad drift av elkraftsystemet efter omfattande störningar som utveckling av nya nyckeltal, prognosmetoder och styrstrategier för att mäta, analysera och förbättra elkraftsystemets förmåga att upprätthålla leveransen av el under ansträngda förhållanden. Arbetet sker i nära samverkan med energibranschen och omfattar tillämpningar i simuleringsverktyg. Projekten genomförs inom kompetenscentret RESILIENT, ett nationellt forskningscentrum som samlar akademi, industri och samhällsaktörer för att utveckla framtidens resilienta och hållbara energisystem genom nära samverkan mellan forskning och tillämning.

Arbetsuppgifter

• Bedriva forskning inom resilienta elkraftsystem med fokus på elsystemets funktion, drift och återgång under kris-, krigs- och andra ansträngda driftförhållanden.
• Utveckla metoder, modeller och beslutsstöd för att stärka elkraftsystemets robusthet, resiliens och återhämtningsförmåga.
• Genomföra teoretiska studier i kombination med modellutveckling, systemsimuleringar och scenarioanalyser för att validera forskningsresultat.
• Använda och vidareutveckla modeller i simuleringsverktyg såsom PowerFactory, PowerWorld och PSS®E eller motsvarande.
• Analysera frågor kopplade till systemdrift, systemåterhämtning, resiliensmått, prognoser och styrstrategier för framtidens elkraftsystem.
• Publicera forskningsresultat i vetenskapliga tidskrifter och presentera resultaten vid nationella och internationella konferenser.
• Samverka med industri, myndigheter och andra forskningsaktörer inom kompetenscentret RESILIENT.

Undervisning och övrig institutionstjänstgöring kan komma att ingå i arbetsuppgifterna, dock max 20% av arbetstiden.

Observera att detta är en förkortad version av annonsen. För att se den fullständiga annonsen vänligen klicka på ”Ansök här” eller se Uppsala universitets hemsida:https://uu.se/jobb/

Automated Image Analysis for Advanced Metabolic Phenotyping in Obesity and Diabetes

About the Project:

You will join PREFERENCE, an international Marie Skłodowska-Curie doctoral network dedicated to advancing large axial field of view (LAFOV) PET/CT imaging. PREFERENCE brings together 12 academic institutions and several industrial partners with extensive expertise in quantitative imaging, image analysis and imaging technology.

A highly innovative system, called long axial field of view (LAFOV) PET/CT, has become available and is the ideal medical imaging modality to study diseases and molecular processes at the whole body/systems biology level with multiple radiotracers. Studying diseases and diagnosing patients using PET/CT imaging should use a whole body/systems biology approach, i.e., a comprehensive whole-body characterization of disease, and it should be longitudinal and should use multiple radiotracers. However, LAFOV PET/CT is so new that we lack the necessary tools, methodologies, imaging procedures and skilled scientists to effectively address key applications in patient care and research. With the PREFERENCE project we aim to develop innovative LAFOV PET/CT methodologies to perform and support ground-breaking new clinical research.

PREFERENCE will train the next generation of researchers specialized in LAFOV PET/CT who will capitalize on the new clinical and research opportunities of the LAFOV PET/CT system. By performing research in both academia and industrial groups, researchers within PREFERENCE receive training in a unique combination of (soft) skills across disciplines and sectors. PREFERENCE will develop new LAFOV PET/CT methodologies and perform LAFOV PET/CT clinical studies across disease areas to obtain novel biological insights. This project was selected by the EU as worthy of funding under the H2025 Marie Sklodowska Curie awards. The consortium consists of 12 academic partners with a strong expertise in quantitative (LAFOV) PET/CT imaging as well as industrial partners developing imaging equipment or providing multi-center image analysis solutions and services.

About the PhD Position:

This is a 4-year full time position as an early stage researcher (ESR) under the auspice of the MSCA DN programme. The successful candidate will have a software background and interest in medical imaging. The candidate will develop tools for accurate analysis of whole-body metabolic imaging, including insulin sensitivity and perfusion assessment and develop spatial correlation tools for visual and quantitative comparisons. The candidate will then apply this to clinical trial data to aid in understanding the multiplexed data and characterise groups with and without metabolic disease, as well as study differences in end organ involvement between sexes, disease states, and other parameters. The aim is to achieve advanced metabolic phenotyping in obesity and diabetes to improve understanding the relationship to mechanisms in relation to end organ damage.

Within the course of this project, there will be 1-month secondments to PREFERENCE partners Aarhus, Copenhagen and Vienna for subprojects and data and software exchange facilitation.

You will receive a monthly gross allowance starting at €2900 - €3100, with an annual increase throughout the programme. The allowance is based on criteria set by the PREFERENCE programme and adjusted with a country-specific correction factor. If applicable, fellows may also be eligible for an additional family allowance of €300 - €360 per month.

Requirements and Qualifications:

To meet the entry requirements for doctoral studies, you must have:

• Successfully completed studies in Physics, Biomedical Engineering, Computer Science or alike (MSc degree or equivalent)

• Very good command of the English language

• Good communication skills (a pre-requisite for cooperating in a multi-disciplinary environment)

• Willingness to travel and flexibility to arrange that in predetermined time

• Proficiency in Python for medical image analysis will be of benefit, and proficiency in C/C++ or similar for efficient management of large images will be of benefit

• Prior experience with medical imaging, CT, PET, MRI, image analysis, and software development will be of benefit.

Note: Important strict eligibility criteria according to MARIE SKLODOWSKA CURIE programs:

Recruitment process:

After assessing compliance with the mobility rule and eligibility for the position based on your Europass CV, motivation letter, and answer to mandatory questions, the selection of the candidates and invitation for the interviews will be done by Antaros. The recruitment process will include online interviews with key stakeholders from Antaros Medical, an international scientific mentor from the network, and a business coach.

As part of the recruitment process, your application will be shared with the PREFERENCE project coordinator for the purpose of verifying eligibility criteria, centralized coordination, and registration of the recruitment process.

You application may also be shared with supervisors at other partner institutions and organisations to assess suitability for similar doctoral positions within the network. Such sharing will only take place in accordance with applicable data protection legislation and the candidate's consent.

Applications should be submitted online by 18 October 2026.

In case of any questions regarding the PhD project, please contact: joel.kullberg@antarosmedical.com

In case of any procedural questions, please contact the coordinator: preference@amsterdamumc.nl